• DocumentCode
    2141617
  • Title

    Detecting deception in testimony

  • Author

    Little, A. ; Skillicorn, D.B.

  • Author_Institution
    Sch. of Comput., Queen´´s Univ., Kingston, ON
  • fYear
    2008
  • fDate
    17-20 June 2008
  • Firstpage
    13
  • Lastpage
    18
  • Abstract
    Several models for deception in text, based on changes in usage frequency of certain classes of words, have been proposed. These are empirically derived from settings in which individuals are asked to lie or be truthful in freeform text. We consider the problem of detecting deception in testimony, where the content generated must necessarily be responsive to questions, where there is the opportunity for immediate followup if the possibility of deception is detected by the questioner, and where those who have reasons to be deceptive have time and motivation to rehearse potential answers. Using the testimony to the Gomery Commission, a situation in which many witnesses had some motivation to be deceptive, we propose and validate a model for deception in testimony. We achieve substantial (80%) agreement with media estimates of who was motivated to testify in a deceptive way.
  • Keywords
    law administration; text analysis; Gomery Commission testimony; psychology; testimony deception detection; text analysis; Artificial intelligence; Frequency; Humans; Internet; Mutual information; Statistical analysis; Statistical distributions; Testing; Uniform resource locators; Yarn;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligence and Security Informatics, 2008. ISI 2008. IEEE International Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    978-1-4244-2414-6
  • Electronic_ISBN
    978-1-4244-2415-3
  • Type

    conf

  • DOI
    10.1109/ISI.2008.4565022
  • Filename
    4565022